Exploiting a Natural Network Effect for Scalable, Fine-grained Clock Synchronization

Nanosecond-level clock synchronization can be an enabler of a new spectrum of timing- and delay-critical applications in data centers. However, the popular clock synchronization algorithm, NTP, can only achieve millisecond-level accuracy. Current solutions for achieving a synchronization accuracy of 10s-100s of nanoseconds require specially designed hardware throughout the network for combatting random network delays and component noise or to exploit clock synchronization inherent in Ethernet standards for the PHY.

In this paper, we present HUYGENS, a software clock synchronization system that uses a synchronization network and leverages three key ideas. First, coded probes identify and reject impure probe data—data captured by probes which suffer queuing delays, random jitter, and NIC timestamp noise. Next, HUYGENS processes the purified data with Support Vector Machines, a widely-used and powerful classifier, to accurately estimate one-way propagation times and achieve clock synchronization to within 100 nanoseconds. Finally, HUYGENS exploits a natural network effect—the idea that a group of pair-wise synchronized clocks must be transitively synchronized— to detect and correct synchronization errors even further.

Through evaluation of two hardware testbeds, we quantify the imprecision of existing clock synchronization across server-pairs, and the effect of temperature on clock speeds. We find the discrepancy between clock frequencies is typically 5-10μs/sec, but it can be as much as 30μs/sec. We show that HUYGENS achieves synchronization to within a few 10s of nanoseconds under varying loads, with a negligible overhead upon link bandwidth due to probes. Because HUYGENS is implemented in software running on standard hardware, it can be readily deployed in current data centers.